Super-resolution imaging

S.J. van der Walt

Applied Mathematics
Stellenbosch University
Private Bag X1, 7602 Matieland, South Africa

Dissertation: PhDEng December 2010

Super-resolution imaging is the process whereby several low-resolution photographs of an object are combined to form a single high-resolution estimation. We investigate each component of this process: image acquisition, registration and reconstruction. A new feature detector, based on the discrete pulse transform, is developed. We show how to implement and store the transform efficiently, and how to match the features using a statistical comparison that improves upon correlation under mild geometric transformation. To simplify reconstruction, the imaging model is linearised, whereafter a polygon-based interpolation operator is introduced to model the underlying camera sensor. Finally, a large, sparse, over-determined system of linear equations is solved, using regularisation. The software developed to perform these computations is made available under an open source license, and may be used to verify the results.